The sale amounts of individual articles of commerce or goods may be recited as important information for store management. The sale amounts of individual goods significantly influence the laying-in quantity of articles and inventory and hence the store management.
Thus the chief or manager of a store is concerned with how to predict the inventory and the laying-in quantity for tomorrow, one week ahead or one month ahead, and formulates a daily, weekly or monthly schedule based on such estimation or prediction of the sale amounts.
That is, if the sale amounts of the individual articles could be estimated with more or less precision, it becomes possible to map out a plan for stocking a proper quantity of articles or to maintain proper inventory with certain efficacy to contribute to cost saving or efficient store management.
At present, sale amount estimation by a store or chief is generally unscientific and inaccurate because it is made in a majority of cases based on experiences, that is, by taking account of various factors possibly influencing the sale volume of the individual articles, such as day of the week, entertainments, weather, temperature, distribution of advertisements or price changes.
However, an advanced artifice in mathematical statistics and analytic skill are required if sale volume estimation is to be made by scientific methods. If, for example, a pre-existing statistic software is used, since computer software packages now on the market are intended for expert users and sold as a software package premised on general application, such as a statistic package or a multi-variable analytic package, the operation is specialized and difficult while it is necessary to employ plural packages in combination. Consequently, it is very difficult for an amateur having no specialized knowledge in statistics, such as store foremen or manager, to master the packages easily. If a model formulation for sale volume estimation of individual articles is left to specialized consultants, it is necessary to take account of the difference in postulates from store to store or modifications imposed by environmental changes for one and the same store. Besides, model maintenance is also difficult to achieve and, if such maintenance is neglected, estimation accuracy is necessarily lowered because of failure in model adaptation.
The JP Patent KOKAI Publication 2-155067 discloses an inventory warning method and system for estimating the sale progress for each article, finding an index for evaluating inventory surplus or deficit at the current time based on the estimated results, and rearraying the information concerning the articles based on the indices, as well as deciding validity of the information concerning the articles based on the hysteresis of measures taken in connection with the inventory or the contents of contracts with customers. This prior-art method, however, lacks in statistical analyses, and is simply based on transition patterns as found from the relation between the time and the total sale volume ratio. On the other hand, estimation is not fully automated because estimation of the sale volume as a function of weather or possible entertainments is subject to decisions by store foremen.
Besides, store personnel not having a specialized knowledge in statistics frequently are unable to become aware of the fact that certain factors possibly influencing the sale volume of individual articles could be utilized as statistic causals. Next, possible causal types cannot be enumerated without considerable difficulties. In addition, it is extremely difficult for an amateur to give a correct judgment as to which of the causals enumerated could actually influence the sale volume (testing or verification of significance of causals). The result is that important causals tend to be disregarded or causals irrelevant to estimation tend to be taken into account to lower the estimation accuracy.
On the other hand, orders for restocking or replenishment are placed on the basis of the state of inventory or inspiration or experiences of the personnel in charge of ordering. Thus the inventory management is an operation in need of skill and depends of dexterity on the personnel in charge of placing restocking orders.
Meanwhile, under the present state of shortage in man-power, the operation of placing orders for replenishment is frequently taken charge of by unskilled operators of part-time workers, which leads to inefficient inventory management.
In view of the above-depicted status of the art, it is an object of the present invention to provide a method for classifying sale amount characteristics, a method for estimating the sale amount, a method for ordering for restocking, a system for classifying sale amount characteristics and a system for ordering for restocking, whereby the sale volume of individual articles may be easily predicted by automatically classifying characteristics of the individual articles, and whereby sale amount characteristics of individual articles may be classified and estimated responsive to differences in postulates from store to store or modification of estimation formula accompanying environmental changes to enable optimum ordering for restocking based on the estimated sale amount of the individual articles.